Evolutionary Synthesis Algorithm - Genetic Operators Tuning
نویسندگان
چکیده
This paper presents the evaluation and fine-tuning of different values of genetic operators in the process of optimizing the designs of the integrated circuits. Due to the increasing usage of the evolutionary optimization in the area of the integrated circuit design, there is a need to find a proper combination of genetic operators parameters’ value. We investigated the interdependence of various values of these parameters and their influence on the quality of the final solution. Generally, the quality of solution is influenced by parameters and the input design. Therefore, it is important to perform this kind of evaluation each time we are searching the optimal values of the genetic operators for some new problem to be solved. Key-Words: evolutionary, scheduling, allocation, genetic operators, tuning
منابع مشابه
Prediction of Surface Roughness by Hybrid Artificial Neural Network and Evolutionary Algorithms in End Milling
Machining processes such as end milling are the main steps of production which have major effect on the quality and cost of products. Surface roughness is one of the considerable factors that production managers tend to implement in their decisions. In this study, an artificial neural network is proposed to minimize the surface roughness by tuning the conditions of machining process such as cut...
متن کاملThe parameters tuning for evolutionary synthesis algorithm
This paper covers the evaluation and fine-tuning of different values of genetic operator’s parameters in the process of optimizing the designs of the integrated circuits. We investigated the interdependence of various values of these parameters in the use over the set of test-bench circuits, as well as their influence on the quality of the final solution and the convergence speed. Due to the in...
متن کاملA Continuous Plane Model to Machine Layout Problems Considering Pick-Up and Drop-Off Points: An Evolutionary Algorithm
One of the well-known evolutionary algorithms inspired by biological evolution is genetic algorithm (GA) that is employed as a robust and global optimization tool to search for the best or near-optimal solution with the search space. In this paper, this algorithm is used to solve unequalsized machines (or intra-cell) layout problems considering pick-up and drop-off (input/output) points. Such p...
متن کاملProposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms
In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...
متن کاملFuzzy logic controlled differential evolution to solve economic load dispatch problems
In recent years, soft computing methods have generated a large research interest. The synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. A particular evolutionary algorithm (EA) is differential evolution (DE). As for any EA, DE algorithm also requires parameters tuning to achieve desirable performance. In this paper tuning the perturbation factor vector of DE ...
متن کامل